| In the process of manufacturing,assembly and use of electrical equipment,there are inevitably uncertainties such as manufacturing deviations,differences in material properties,changes in the working environment and other uncertainties.Uncertainties often make the actual parameters of electrical equipment deviate from the original design value,thus making the product performance decline,and even accidents occur.In order to mitigate the negative impact of uncertainties on electrical equipment,and to balance the relationship between reliability,robustness and other performance indicators of electrical equipment,it is necessary to consider the uncertainties in engineering during the optimal design phase of electrical products.Under the premise of robustness and reliability,this thesis mainly accomplishes the following work in order to solve the standard problem of testing electromagnetic field analysis method,permanent magnet magic ring in electrical equipment and optimization problem in permanent magnet synchronous motor in electrical engineering field.Firstly,in order to ensure the reliability and robustness of electrical equipment under the influence of uncertainties,a scientific optimal weight-assisted optimal design method（ω-RBRDO）that takes into account both reliability and robustness is investigated in this thesis.This method takes into account both reliability and robustness indicators to ensure the reliability of the sought design solution by making the constraints satisfied with a certain probability,and introduces the idea of optimal weights in order to find the proportional coefficients that optimize the two indicators of robustness and target performance.In this thesis,the optimal weights are selected using the images set method,which takes into account the differences in order of importance among the objective functions and can effectively improve the accuracy of the optimal design method.Secondly,the optimal design method based on ω-RBRDO is verified numerically.Theω-RBRDO method is combined with the particle swarm optimization algorithm,and two analytical functions are used to validate it separately.The optimization results are compared with the optimization results of deterministic optimization design,reliability-based optimization design,robust optimization design,and the references to demonstrate the effectiveness of the ω-RBRDO method in ensuring the robustness and reliability of the optimized design solution.Finally,the method is applied to the standard problem of testing electromagnetic field analysis methods in the field of electrical engineering,permanent magnet magic rings and permanent magnet synchronous motors in electrical equipment.For the standard problem,a design solution is sought to minimize the stray field while the energy is closer to 180 MJ without losing superconductor,while taking into account the robustness and reliability.For the permanent magnet magic ring problem,in the case of magnetic flux density amplitude fluctuation less than 1.8T,the average value of the magnetic flux density amplitude of the central air gap is optimized to maximize it.For the motor problem,a 3k W ferrite permanent magnet synchronous motor is selected to optimize its average torque at peak current.Under the requirement of torque pulsation kr≤3%,the width and length of the motor permanent magnet and the angle of the V-shape are designed to meet the requirements of maximizing the average torque at the peak current of the motor.The optimal design method based onω-RBRDO improves the stability of the design scheme by considering the influence of uncertainties,and improves the status quo of considering only one kind of index in the past due to the comprehensive consideration of both robustness and reliability,which is a guiding meaning for the refined design and production of high performance motors in the future. |
